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Exercise Prescription Based On A Six-Minute Walk Test In Survivors Of Childhood Acute Lymphoblastic Leukemia

2023· article· en· W4387063005 on OpenAlexaff
E Bertrand, Maxime Caru, Caroline Laverdière, Maja Krajinović, Daniel Sinnett, Daniel Curnier

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2023
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
Fundersnot available
KeywordsMedicineVentilatory thresholdRating of perceived exertionExercise prescriptionIntensity (physics)Cardiopulmonary exercise testPhysical therapyHeart rateLymphoblastic LeukemiaInternal medicineVO2 maxLeukemiaBlood pressure

Abstract

fetched live from OpenAlex

Exercise is beneficial for cancer patients and survivors. Individualized training intensities should be prescribed according to variables determined from a maximal cardiopulmonary exercise test. However, access to this technology is limited. The Six-Minute Walk Test (6MWT) is a valid and safe field test for assessing aerobic capacity in childhood acute lymphoblastic leukemia (ALL) survivors. PURPOSE: The first aim of this study was to propose a specific 6MWT equation to predict ventilatory threshold in childhood ALL survivors. The second objective was to compare measured heart rate (HR) at ventilatory threshold with recommended exercise intensity levels for cancer patients and survivors. METHODS: Childhood ALL survivors (n = 154) completed a 6MWT and a maximal cardiopulmonary exercise test with gas exchange analysis. Participants were randomized into 2 groups to predict the ventilatory threshold equation (n = 107) and to validate it (n = 47). Backward linear regression analyses were used to determine the prediction equation. The root mean square error (RMSE) was used to measure the accuracy of the predicted HR at ventilatory threshold on the validation group. Measured HR at ventilatory threshold were compared to moderate intensity (40-59% HR reserve (HRR)) and vigorous intensity (60-89% HRR). RESULTS: The equation was [HR ventilatory threshold = (0.074 x age) + (0.218 x HR end 6MWT) + (0.016 x cumulative doxorubicin dose) - (0.051 x height) - (0.835 x years since the end of treatment) - (0.115 x physical activity level) + (0.010 x distance 6MWT) + (0.142 x HR rest) - (0.492 x rating of perceived exertion) + 126.79] (p = 0.001, R2 = 0.271). The resulting RMSE was 14.5 bpm. Four participants had their ventilatory threshold below 40% HRR, 37 between 40-59% HRR, 100 between 60-89% HRR, and 11 above 89% HRR (median HR at ventilatory threshold 70.8% HRR; range 16.4-118.9% HRR). CONCLUSION: These results reinforce the utility of assessing the functional capacity of patients with a 6MWT to propose an individualized training program without maximal exercise test. The high heterogeneity in ventilatory thresholds by %HRR may explain the different training responses by %HRR. A training intensity based on a percentage of ventilatory threshold would be appropriate if maximal exercise test is not available for childhood ALL survivors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.284
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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